Molecular Determinants of Atherosclerotic Cardiovascular Disease in Multi-ethnic Populations

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ABSTRACT Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of death worldwide. Understanding the process of atherosclerosis and its progression is essential to decrease ASCVD burden. Despite successful identification of genetic variants and clinical risk factors related to ASCVD over the last decade, the underlying mechanism - how genetic variants and human metabolism contribute to atherosclerosis remains unclear. Circulating metabolites, the ultimate products of gene and environment interaction, holds promise to link genetic variants, circulating metabolites to atherosclerosis. We previous work has shown that circulating metabolites involved in lipids and oxidation metabolism and their genetic determinants predict the onset of ASCVD. Few studies have examined the metabolic influence on atherosclerosis in multi-ethnic populations, and the effect of longitudinal metabolomic changes on atherosclerosis. Our overall objective is to identify circulating metabolite and its longitudinal change, along with the genetic determinants, contributing to atherosclerosis and ASCVD in middle and late life among multi-ethnic populations. We propose to conduct this project in six studies from the Trans-Omics for Precision Medicine (TOPMed) Program, including European, African and Hispanic Americans. We will leverage the unique resources from each study on whole genome sequencing (WGS) data, metabolome profiles, and atherosclerotic traits, and use TOPMed Cloud Computing as the computational engine. Our aims are: (1) to identify circulating metabolite and it change associated with ASCVD risk; (2) to determine circulating metabolite and it change associated subclinical atherosclerosis and its progression; and (3) to characterize genetic architecture of ASCVD metabolites and evaluate its association with ASCVD risk. Our team is uniquely positioned, given our expertise in ASCVD pathophysiology, metabolome profiling, genomics, biostatistics and bioinformatics. The results of this research will enable continued scientific progress toward an understanding of ASCVD etiology, with direct implications for prevention and potential therapies.